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Optimal Access Points Selection Based on Mobility Prediction in Heterogeneous Small Cell Networks

机译:异构小蜂窝网络中基于移动性预测的最佳接入点选择

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While increasing access points(APs) densification is considered as a useful solution to cater for the explosive growth of throughput demands, its impact on the handover needs to be carefully handled. In order to reduce unnecessary handover and improve the users' experience, this paper proposes an optimal AP selection algorithm for the mobile user based on mobility prediction. According to the historical data of the mobile user, we use a semi-Markov model with finite conditions to predict the user's next possible location. Then, according to the user's demand for network resources, the most suitable AP is selected based on the proposed optimization model in the expected location. The proposed handover scheme selects the best AP connectivity, by skipping handover of some APs along the moving trajectory. Simulation results show that the proposed scheme achieves a better performance compared with existing schemes in terms of the prediction accuracy.
机译:虽然增加接入点(AP)的密度被认为是满足吞吐量需求爆炸性增长的有用解决方案,但需要谨慎处理其对切换的影响。为了减少不必要的切换并改善用户体验,本文提出了一种基于移动性预测的移动用户最佳AP选择算法。根据移动用户的历史数据,我们使用具有有限条件的半马尔可夫模型来预测用户的下一个可能位置。然后,根据用户对网络资源的需求,基于建议的优化模型在预期的位置选择最合适的AP。所提出的切换方案通过跳过沿移动轨迹的一些AP的切换来选择最佳的AP连接。仿真结果表明,与现有方案相比,该方案具有更好的预测精度。

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